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@@ -244,7 +244,7 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
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@@ -254,7 +254,7 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 1 minutes 52.819 seconds)
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**Total running time of the script:** ( 1 minutes 54.033 seconds)
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.. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:
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.. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:
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@@ -286,17 +286,17 @@ We will then compare its performance against (1) :code:`torch.softmax` and (2) t
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softmax-performance:
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softmax-performance:
|
||||||
N Triton Torch (native) Torch (jit)
|
N Triton Torch (native) Torch (jit)
|
||||||
0 256.0 512.000001 546.133347 188.321838
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0 256.0 512.000001 546.133347 186.181817
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1 384.0 585.142862 585.142862 151.703707
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1 384.0 585.142862 585.142862 153.600004
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2 512.0 655.360017 606.814814 154.566038
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2 512.0 630.153853 606.814814 154.566038
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3 640.0 660.645170 640.000002 160.000000
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3 640.0 682.666684 640.000002 160.000000
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4 768.0 702.171410 664.216187 162.754967
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4 768.0 702.171410 664.216187 163.839992
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.. ... ... ... ...
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93 12160.0 810.666687 405.755985 199.038365
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94 12288.0 810.754644 415.661740 199.197579
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[98 rows x 4 columns]
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@@ -314,7 +314,7 @@ In the above plot, we can see that:
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 3 minutes 29.348 seconds)
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**Total running time of the script:** ( 3 minutes 30.656 seconds)
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.. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:
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.. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:
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@@ -462,37 +462,37 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
|
|||||||
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||||||
matmul-performance:
|
matmul-performance:
|
||||||
M cuBLAS ... Triton Triton (+ LeakyReLU)
|
M cuBLAS ... Triton Triton (+ LeakyReLU)
|
||||||
0 256.0 2.730667 ... 2.978909 2.978909
|
0 256.0 2.978909 ... 2.978909 2.978909
|
||||||
1 384.0 7.372800 ... 8.507077 8.507077
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1 384.0 7.372800 ... 8.507077 8.507077
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2 512.0 14.563555 ... 16.384000 16.384000
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2 512.0 14.563555 ... 16.384000 16.384000
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3 640.0 22.260869 ... 24.380953 24.380953
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3 640.0 22.260869 ... 24.380953 24.380953
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4 768.0 32.768000 ... 34.028308 34.028308
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4 768.0 32.768000 ... 34.028308 34.028308
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5 896.0 37.971025 ... 40.140799 39.025776
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5 896.0 39.025776 ... 40.140799 39.025776
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6 1024.0 49.932191 ... 53.773130 52.428801
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6 1024.0 49.932191 ... 53.773130 52.428801
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7 1152.0 44.566925 ... 46.656000 45.938215
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7 1152.0 44.566925 ... 46.656000 45.938215
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8 1280.0 51.200001 ... 56.109587 56.109587
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8 1280.0 51.200001 ... 56.109587 56.109587
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9 1408.0 64.138541 ... 66.485074 66.485074
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9 1408.0 64.138541 ... 66.485074 65.684049
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10 1536.0 80.430545 ... 78.643199 78.643199
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11 1664.0 63.372618 ... 62.492442 62.061463
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11 1664.0 63.372618 ... 62.929456 62.061463
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12 1792.0 72.983276 ... 72.047592 71.588687
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13 1920.0 69.120002 ... 70.530615 70.530615
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14 2048.0 73.908442 ... 76.959706 76.608294
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14 2048.0 73.908442 ... 76.608294 76.260072
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15 2176.0 83.500614 ... 85.998493 85.632545
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16 2304.0 68.446623 ... 76.809875 76.563695
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16 2304.0 68.251065 ... 77.307030 76.076024
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17 2432.0 71.305746 ... 74.719317 84.367759
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17 2432.0 71.125224 ... 84.115159 84.621881
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18 2560.0 77.833728 ... 80.709358 80.313727
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18 2560.0 78.019048 ... 81.108913 80.908642
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||||||
19 2688.0 83.552988 ... 88.836198 89.676257
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19 2688.0 83.369354 ... 89.254248 88.011732
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20 2816.0 84.035084 ... 83.552120 83.392363
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20 2816.0 81.218262 ... 83.873477 82.759409
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21 2944.0 81.967162 ... 83.198715 81.298583
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21 2944.0 82.921853 ... 82.102191 82.237674
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22 3072.0 81.943708 ... 89.170242 88.335577
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22 3072.0 81.238312 ... 88.060814 87.924073
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||||||
23 3200.0 83.116885 ... 94.814812 94.395283
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23 3200.0 84.656085 ... 95.380032 95.522391
|
||||||
24 3328.0 82.275764 ... 84.895397 84.397770
|
24 3328.0 82.939284 ... 84.003845 84.003845
|
||||||
25 3456.0 82.519518 ... 91.407671 88.304015
|
25 3456.0 79.430113 ... 91.097818 87.536988
|
||||||
26 3584.0 86.540320 ... 87.548840 94.448944
|
26 3584.0 86.540320 ... 94.747514 96.579370
|
||||||
27 3712.0 83.947349 ... 86.117243 87.590836
|
27 3712.0 85.675250 ... 88.092894 87.629253
|
||||||
28 3840.0 83.465663 ... 84.679936 91.701494
|
28 3840.0 83.465663 ... 84.354966 91.398346
|
||||||
29 3968.0 86.053553 ... 90.859224 85.932350
|
29 3968.0 86.053553 ... 91.062642 86.849777
|
||||||
30 4096.0 93.271527 ... 88.359266 86.313653
|
30 4096.0 93.142072 ... 83.468735 82.342167
|
||||||
|
|
||||||
[31 rows x 5 columns]
|
[31 rows x 5 columns]
|
||||||
|
|
||||||
@@ -502,7 +502,7 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
|
|||||||
|
|
||||||
.. rst-class:: sphx-glr-timing
|
.. rst-class:: sphx-glr-timing
|
||||||
|
|
||||||
**Total running time of the script:** ( 6 minutes 28.869 seconds)
|
**Total running time of the script:** ( 6 minutes 33.543 seconds)
|
||||||
|
|
||||||
|
|
||||||
.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
|
.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
|
||||||
|
@@ -238,7 +238,7 @@ References
|
|||||||
|
|
||||||
.. rst-class:: sphx-glr-timing
|
.. rst-class:: sphx-glr-timing
|
||||||
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|
||||||
**Total running time of the script:** ( 0 minutes 0.016 seconds)
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**Total running time of the script:** ( 0 minutes 0.365 seconds)
|
||||||
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|
||||||
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|
||||||
.. _sphx_glr_download_getting-started_tutorials_04-low-memory-dropout.py:
|
.. _sphx_glr_download_getting-started_tutorials_04-low-memory-dropout.py:
|
||||||
|
@@ -5,14 +5,14 @@
|
|||||||
|
|
||||||
Computation times
|
Computation times
|
||||||
=================
|
=================
|
||||||
**11:51.052** total execution time for **getting-started_tutorials** files:
|
**11:58.596** total execution time for **getting-started_tutorials** files:
|
||||||
|
|
||||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||||
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 06:28.869 | 0.0 MB |
|
| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 06:33.543 | 0.0 MB |
|
||||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||||
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 03:29.348 | 0.0 MB |
|
| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 03:30.656 | 0.0 MB |
|
||||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||||
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 01:52.819 | 0.0 MB |
|
| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 01:54.033 | 0.0 MB |
|
||||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||||
| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``) | 00:00.016 | 0.0 MB |
|
| :ref:`sphx_glr_getting-started_tutorials_04-low-memory-dropout.py` (``04-low-memory-dropout.py``) | 00:00.365 | 0.0 MB |
|
||||||
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
+---------------------------------------------------------------------------------------------------------+-----------+--------+
|
||||||
|
@@ -333,12 +333,12 @@ for different problem sizes.</p>
|
|||||||
10 4194304.0 780.190482 780.190482
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||||||
11 8388608.0 812.429770 812.429770
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|
||||||
12 16777216.0 833.084721 833.084721
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12 16777216.0 833.084721 833.084721
|
||||||
13 33554432.0 842.004273 842.004273
|
13 33554432.0 842.004273 843.811163
|
||||||
14 67108864.0 847.448255 848.362445
|
14 67108864.0 847.448255 848.362445
|
||||||
15 134217728.0 849.737435 850.656574
|
15 134217728.0 849.737435 850.656574
|
||||||
</pre></div>
|
</pre></div>
|
||||||
</div>
|
</div>
|
||||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 52.819 seconds)</p>
|
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 1 minutes 54.033 seconds)</p>
|
||||||
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-01-vector-add-py">
|
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-01-vector-add-py">
|
||||||
<div class="sphx-glr-download sphx-glr-download-python docutils container">
|
<div class="sphx-glr-download sphx-glr-download-python docutils container">
|
||||||
<p><a class="reference download internal" download="" href="../../_downloads/62d97d49a32414049819dd8bb8378080/01-vector-add.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">01-vector-add.py</span></code></a></p>
|
<p><a class="reference download internal" download="" href="../../_downloads/62d97d49a32414049819dd8bb8378080/01-vector-add.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">01-vector-add.py</span></code></a></p>
|
||||||
|
@@ -373,17 +373,17 @@ We will then compare its performance against (1) <code class="code docutils lite
|
|||||||
<p class="sphx-glr-script-out">Out:</p>
|
<p class="sphx-glr-script-out">Out:</p>
|
||||||
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>softmax-performance:
|
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>softmax-performance:
|
||||||
N Triton Torch (native) Torch (jit)
|
N Triton Torch (native) Torch (jit)
|
||||||
0 256.0 512.000001 546.133347 188.321838
|
0 256.0 512.000001 546.133347 186.181817
|
||||||
1 384.0 585.142862 585.142862 151.703707
|
1 384.0 585.142862 585.142862 153.600004
|
||||||
2 512.0 655.360017 606.814814 154.566038
|
2 512.0 630.153853 606.814814 154.566038
|
||||||
3 640.0 660.645170 640.000002 160.000000
|
3 640.0 682.666684 640.000002 160.000000
|
||||||
4 768.0 702.171410 664.216187 162.754967
|
4 768.0 702.171410 664.216187 163.839992
|
||||||
.. ... ... ... ...
|
.. ... ... ... ...
|
||||||
93 12160.0 810.666687 405.755985 199.038365
|
93 12160.0 810.666687 406.179533 199.038365
|
||||||
94 12288.0 810.754644 415.661740 199.197579
|
94 12288.0 810.754644 415.881552 199.298541
|
||||||
95 12416.0 809.189387 412.149375 198.954424
|
95 12416.0 809.189387 412.149375 198.904612
|
||||||
96 12544.0 807.661970 412.971190 199.111113
|
96 12544.0 807.661970 412.971190 199.111113
|
||||||
97 12672.0 807.776923 412.516771 199.167004
|
97 12672.0 806.170993 412.097543 199.264875
|
||||||
|
|
||||||
[98 rows x 4 columns]
|
[98 rows x 4 columns]
|
||||||
</pre></div>
|
</pre></div>
|
||||||
@@ -396,7 +396,7 @@ We will then compare its performance against (1) <code class="code docutils lite
|
|||||||
Note however that the PyTorch <cite>softmax</cite> operation is more general and will works on tensors of any shape.</p></li>
|
Note however that the PyTorch <cite>softmax</cite> operation is more general and will works on tensors of any shape.</p></li>
|
||||||
</ul>
|
</ul>
|
||||||
</div></blockquote>
|
</div></blockquote>
|
||||||
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 29.348 seconds)</p>
|
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 3 minutes 30.656 seconds)</p>
|
||||||
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-02-fused-softmax-py">
|
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-02-fused-softmax-py">
|
||||||
<div class="sphx-glr-download sphx-glr-download-python docutils container">
|
<div class="sphx-glr-download sphx-glr-download-python docutils container">
|
||||||
<p><a class="reference download internal" download="" href="../../_downloads/d91442ac2982c4e0cc3ab0f43534afbc/02-fused-softmax.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">02-fused-softmax.py</span></code></a></p>
|
<p><a class="reference download internal" download="" href="../../_downloads/d91442ac2982c4e0cc3ab0f43534afbc/02-fused-softmax.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">02-fused-softmax.py</span></code></a></p>
|
||||||
|
@@ -567,42 +567,42 @@ torch_output=tensor([[ 1.1045, -36.9688, 31.4688, ..., -11.3906, 24.4531, -3
|
|||||||
<p class="sphx-glr-script-out">Out:</p>
|
<p class="sphx-glr-script-out">Out:</p>
|
||||||
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>matmul-performance:
|
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>matmul-performance:
|
||||||
M cuBLAS ... Triton Triton (+ LeakyReLU)
|
M cuBLAS ... Triton Triton (+ LeakyReLU)
|
||||||
0 256.0 2.730667 ... 2.978909 2.978909
|
0 256.0 2.978909 ... 2.978909 2.978909
|
||||||
1 384.0 7.372800 ... 8.507077 8.507077
|
1 384.0 7.372800 ... 8.507077 8.507077
|
||||||
2 512.0 14.563555 ... 16.384000 16.384000
|
2 512.0 14.563555 ... 16.384000 16.384000
|
||||||
3 640.0 22.260869 ... 24.380953 24.380953
|
3 640.0 22.260869 ... 24.380953 24.380953
|
||||||
4 768.0 32.768000 ... 34.028308 34.028308
|
4 768.0 32.768000 ... 34.028308 34.028308
|
||||||
5 896.0 37.971025 ... 40.140799 39.025776
|
5 896.0 39.025776 ... 40.140799 39.025776
|
||||||
6 1024.0 49.932191 ... 53.773130 52.428801
|
6 1024.0 49.932191 ... 53.773130 52.428801
|
||||||
7 1152.0 44.566925 ... 46.656000 45.938215
|
7 1152.0 44.566925 ... 46.656000 45.938215
|
||||||
8 1280.0 51.200001 ... 56.109587 56.109587
|
8 1280.0 51.200001 ... 56.109587 56.109587
|
||||||
9 1408.0 64.138541 ... 66.485074 66.485074
|
9 1408.0 64.138541 ... 66.485074 65.684049
|
||||||
10 1536.0 80.430545 ... 78.643199 78.643199
|
10 1536.0 80.430545 ... 78.643199 78.643199
|
||||||
11 1664.0 63.372618 ... 62.492442 62.061463
|
11 1664.0 63.372618 ... 62.929456 62.061463
|
||||||
12 1792.0 72.983276 ... 72.047592 71.588687
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12 1792.0 72.983276 ... 72.512412 72.047592
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13 1920.0 69.120002 ... 70.530615 70.530615
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13 1920.0 69.120002 ... 70.172588 70.530615
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14 2048.0 73.908442 ... 76.959706 76.608294
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14 2048.0 73.908442 ... 76.608294 76.260072
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15 2176.0 83.500614 ... 85.998493 85.632545
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15 2176.0 83.155572 ... 85.632545 85.269692
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16 2304.0 68.446623 ... 76.809875 76.563695
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16 2304.0 68.251065 ... 77.307030 76.076024
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17 2432.0 71.305746 ... 74.719317 84.367759
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17 2432.0 71.125224 ... 84.115159 84.621881
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18 2560.0 77.833728 ... 80.709358 80.313727
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18 2560.0 78.019048 ... 81.108913 80.908642
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19 2688.0 83.552988 ... 88.836198 89.676257
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19 2688.0 83.369354 ... 89.254248 88.011732
|
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20 2816.0 84.035084 ... 83.552120 83.392363
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20 2816.0 81.218262 ... 83.873477 82.759409
|
||||||
21 2944.0 81.967162 ... 83.198715 81.298583
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21 2944.0 82.921853 ... 82.102191 82.237674
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22 3072.0 81.943708 ... 89.170242 88.335577
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22 3072.0 81.238312 ... 88.060814 87.924073
|
||||||
23 3200.0 83.116885 ... 94.814812 94.395283
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23 3200.0 84.656085 ... 95.380032 95.522391
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24 3328.0 82.275764 ... 84.895397 84.397770
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24 3328.0 82.939284 ... 84.003845 84.003845
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25 3456.0 82.519518 ... 91.407671 88.304015
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25 3456.0 79.430113 ... 91.097818 87.536988
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26 3584.0 86.540320 ... 87.548840 94.448944
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26 3584.0 86.540320 ... 94.747514 96.579370
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27 3712.0 83.947349 ... 86.117243 87.590836
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27 3712.0 85.675250 ... 88.092894 87.629253
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28 3840.0 83.465663 ... 84.679936 91.701494
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28 3840.0 83.465663 ... 84.354966 91.398346
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29 3968.0 86.053553 ... 90.859224 85.932350
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29 3968.0 86.053553 ... 91.062642 86.849777
|
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30 4096.0 93.271527 ... 88.359266 86.313653
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30 4096.0 93.142072 ... 83.468735 82.342167
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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-03-matrix-multiplication-py">
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<p><a class="reference download internal" download="" href="../../_downloads/d5fee5b55a64e47f1b5724ec39adf171/03-matrix-multiplication.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">03-matrix-multiplication.py</span></code></a></p>
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<p><a class="reference download internal" download="" href="../../_downloads/d5fee5b55a64e47f1b5724ec39adf171/03-matrix-multiplication.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">03-matrix-multiplication.py</span></code></a></p>
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@@ -370,7 +370,7 @@ to explore the <cite>triton/language/random</cite> folder!</p>
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<dd><p>Nitish Srivastava and Geoffrey Hinton and Alex Krizhevsky and Ilya Sutskever and Ruslan Salakhutdinov, “Dropout: A Simple Way to Prevent Neural Networks from Overfitting”, JMLR 2014</p>
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<dd><p>Nitish Srivastava and Geoffrey Hinton and Alex Krizhevsky and Ilya Sutskever and Ruslan Salakhutdinov, “Dropout: A Simple Way to Prevent Neural Networks from Overfitting”, JMLR 2014</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.365 seconds)</p>
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<p><a class="reference download internal" download="" href="../../_downloads/c9aed78977a4c05741d675a38dde3d7d/04-low-memory-dropout.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">04-low-memory-dropout.py</span></code></a></p>
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<p><a class="reference download internal" download="" href="../../_downloads/c9aed78977a4c05741d675a38dde3d7d/04-low-memory-dropout.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">04-low-memory-dropout.py</span></code></a></p>
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<span id="sphx-glr-getting-started-tutorials-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
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<p><strong>11:51.052</strong> total execution time for <strong>getting-started_tutorials</strong> files:</p>
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<tr class="row-odd"><td><p><a class="reference internal" href="03-matrix-multiplication.html#sphx-glr-getting-started-tutorials-03-matrix-multiplication-py"><span class="std std-ref">Matrix Multiplication</span></a> (<code class="docutils literal notranslate"><span class="pre">03-matrix-multiplication.py</span></code>)</p></td>
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<tr class="row-odd"><td><p><a class="reference internal" href="03-matrix-multiplication.html#sphx-glr-getting-started-tutorials-03-matrix-multiplication-py"><span class="std std-ref">Matrix Multiplication</span></a> (<code class="docutils literal notranslate"><span class="pre">03-matrix-multiplication.py</span></code>)</p></td>
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<td><p>06:33.543</p></td>
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<tr class="row-odd"><td><p><a class="reference internal" href="01-vector-add.html#sphx-glr-getting-started-tutorials-01-vector-add-py"><span class="std std-ref">Vector Addition</span></a> (<code class="docutils literal notranslate"><span class="pre">01-vector-add.py</span></code>)</p></td>
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<tr class="row-odd"><td><p><a class="reference internal" href="01-vector-add.html#sphx-glr-getting-started-tutorials-01-vector-add-py"><span class="std std-ref">Vector Addition</span></a> (<code class="docutils literal notranslate"><span class="pre">01-vector-add.py</span></code>)</p></td>
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<tr class="row-even"><td><p><a class="reference internal" href="04-low-memory-dropout.html#sphx-glr-getting-started-tutorials-04-low-memory-dropout-py"><span class="std std-ref">Low-Memory Dropout</span></a> (<code class="docutils literal notranslate"><span class="pre">04-low-memory-dropout.py</span></code>)</p></td>
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